Proceedings of the Annual Meeting of the Cognitive Science Society

This paper describes how inductively produced generalizations can influence the process of belief revision,drawing examples from a computational model of scientific discovery called REVOLVER. This system constructs componential models in chemistry, using techniques from truth maintenance systems to resolve inconsistencies that arise in the course of model formulation. The latter process involves reinterpreting observations(premises) given to the system and selecting the best of several plausible revisions to make. We will see how generalisations aid in such decisions. The choice is made by considering three main factors: the number of models each premise supports, the number of premises supporting the generalized reaction, and whether a proposed revision to that premise matches any predictions made by any generalizations. Based on these factors, a cost is assigned to each premise being considered for revision; the hypothesis (set of revisions) having the lowest cost is chosen as best, and its revisions are carried out. By viewing generalized premise reactions as a pariuligm, we will argue that the revision process of REVOLVER models how scientific paradigms shift over time.